ai-gradio: Easily Integrate Multiple AI Models and Build Multimodal Applications Based on Gradio

General Introduction

ai-gradio is an open source Python toolkit designed to help developers easily integrate and use multiple AI models. Built on Gradio, the project provides a unified interface that supports multiple AI models and services. Whether it's text, speech or video processing, ai-gradio provides the appropriate solution. Its multi-provider support feature allows developers to integrate services from 15+ AI providers including OpenAI, Google Gemini, Anthropic, etc., greatly simplifying the development process of AI applications.

Function List

• Multi-provider support: Integration with 15+ AI providers, including OpenAI, Google Gemini, Anthropic, and more.
• text chat: Provide an interactive chat interface for all text models.
• voice chat: Supports real-time voice interaction with OpenAI models.
• video chat: Provides video processing capabilities with the Gemini model.
• code generation: Provide specialized interfaces for programming assistance.
• multimodal support: Supports text, image and video input.
• Agent Team: Integration with CrewAI to support collaborative AI tasks.
• Browser Automation: AI agents can perform web-based tasks.

Using Help

Installation process

1. Foundation Installation::

   pip install ai-gradio

2. Installation of provider-specific support::
   • OpenAI Support: bash
pip install 'ai-gradio[openai]'

   • Google Gemini Support: bash
pip install 'ai-gradio[gemini]'

   • Anthropic Claude Support: bash
pip install 'ai-gradio[anthropic]'

   • Groq Support: bash
pip install 'ai-gradio[groq]'

   • Install all provider support: bash
pip install 'ai-gradio[all]'


Guidelines for use

1. API Key Configuration: Configure the appropriate API key according to the desired AI provider. Example:

   export OPENAI_API_KEY=
export GEMINI_API_KEY=
export ANTHROPIC_API_KEY=
export GROQ_API_KEY=

2. Creating a Text Chat Application::

   import gradio as gr
from ai_gradio import ChatInterface
chat = ChatInterface(provider='openai', model='gpt-4-turbo')
gr.Interface(fn=chat.chat, inputs="text", outputs="text").launch()

3. Creating Voice Chat Apps::

   import gradio as gr
from ai_gradio import VoiceChatInterface
voice_chat = VoiceChatInterface(provider='openai', model='gpt-4-turbo')
gr.Interface(fn=voice_chat.chat, inputs="microphone", outputs="text").launch()

4. Create video processing applications::

   import gradio as gr
from ai_gradio import VideoChatInterface
video_chat = VideoChatInterface(provider='gemini', model='gemini-pro')
gr.Interface(fn=video_chat.process, inputs="video", outputs="video").launch()

5. Code Generation Application::

   import gradio as gr
from ai_gradio import CodeGenInterface
code_gen = CodeGenInterface(provider='openai', model='gpt-4-turbo')
gr.Interface(fn=code_gen.generate, inputs="text", outputs="code").launch()

6. multimodal support::

   import gradio as gr
from ai_gradio import MultiModalInterface
multi_modal = MultiModalInterface(provider='openai', models=['gpt-4-turbo', 'dall-e'])
gr.Interface(fn=multi_modal.process, inputs=["text", "image"], outputs=["text", "image"]).launch()

7. Agent Teamwork::

   import gradio as gr
from ai_gradio import AgentTeamInterface
agent_team = AgentTeamInterface(provider='crewai', team='Support Team')
gr.Interface(fn=agent_team.collaborate, inputs="text", outputs="text").launch()

8. Browser Automation::

   import gradio as gr
from ai_gradio import BrowserAutomationInterface
browser_agent = BrowserAutomationInterface(provider='openai', model='gpt-4-turbo')
gr.Interface(fn=browser_agent.automate, inputs="text", outputs="text").launch()